Data Cleaning with Python
Skill Path
Learn data cleaning, one of the most crucial skills you need in your data career. You'll learn how to clean, manipulate, and analyze data with Python, one of the most common programming languages. By the end, you will have everything you need-and more-to perform data cleaning from start to finish.
- Beginner friendly
- 4 months (5 hrs/week)
- Self paced
- 9 Courses
- 8 projects
Overview of Python courses
Python skills you'll learn
- ✓ Cleaning and visualizing data
- ✓ Programming with Python to manipulate data
- ✓ Working with missing data
Outline of Python courses
3 steps · 9 courses
Part 1: Introduction to Python [4 courses]
Introduce yourself to the Python programming language.
- Course 1
Introduction to Python Programming
2hDevelop foundational Python programming skills by writing code, working with variables, and processing numerical and text data.
Course Objectives ▾
- Write computer programs using Python
- Save values using variables
- Process numerical data and text data
- Create lists using Python
- Course 2
Basic Operators and Data Structures in Python
5hStrengthen Python fundamentals by using loops, conditional logic, operators, and dictionaries to manipulate data and construct frequency tables.
Course Objectives ▾
- Use for loops to repeat processes and conduct data analysis
- Implement if, else, and elif statements in programming logic
- Employ logical and comparison operators in Python
- Develop and update Python dictionaries for data manipulation
- Construct frequency tables using dictionaries for data analytics
- Course 3
Python Functions and Jupyter Notebook
7hCreate reusable Python functions and run analyses in Jupyter Notebook to organize code, debug logic, and complete portfolio-ready data projects.
Course Objectives ▾
- Write Python functions
- Debug functions
- Define function arguments
- Write functions that return multiple variables
- Employ Jupyter notebook
- Build a portfolio project
- Course 4
Intermediate Python for Data Science
8hStrengthen your Python data science skills by cleaning text data, working with dates and times, and applying object-oriented programming concepts.
Course Objectives ▾
- Clean and analyze text data
- Define object-oriented programming in Python
- Process dates and times
Part 2: Intermediate Python and Pandas [2 courses]
Explore Python and Pandas.
- Course 1
Introduction to Pandas and NumPy for Data Analysis
13hDevelop practical skills with NumPy and pandas to explore, clean, and analyze data efficiently using real datasets and guided practice.
Course Objectives ▾
- Improve your workflow using vectorized operations
- Select data by value using Boolean indexing
- Analyze data using pandas and NumPy
- Course 2
Introduction to Data Visualization in Python
7hApply statistical reasoning to visualization by combining Python plotting tools with sound design choices to communicate patterns, trends, and insights clearly.
Course Objectives ▾
- Visualize time series data with line plots
- Define correlations and visualize them with scatter plots
- Visualize frequency distributions with bar plots and histograms
- Improve your exploratory data visualization workflow using pandas
- Visualize multiple variables using Seaborn's relational plots
Part 3: Data Cleaning in Python [3 courses]
Learn the basics of data cleaning in Python.
- Course 1
Data Cleaning and Analysis in Python
11hPractice cleaning and preparing messy datasets in Python by aggregating, reshaping, and combining data for efficient, real-world analysis.
Course Objectives ▾
- Employ data aggregation techniques
- Combine datasets
- Transform and reshape data
- Clean strings and resolve missing data
- Course 2
Advanced Data Cleaning in Python
8hGo beyond basic data cleaning by working with messy real-world datasets using advanced Python techniques like regex, lambdas, and list comprehensions.
Course Objectives ▾
- Clean and manipulate text data using regular expressions
- Employ lambda functions and list comprehension with pandas
- Resolve missing data
- Course 3
Data Cleaning Project Walkthrough
7hReal datasets are messy. This project-based course walks through cleaning, combining, and preparing data in Python for analysis.
Course Objectives ▾
- Complete a data cleaning project from start to finish
- Improve your data cleaning skills
Python projects you'll build
8 hands-on projects across the path
Star Wars Survey
For this project, you'll become a data analyst exploring FiveThirtyEight's Star Wars survey data. You'll use Python and pandas to map values, compute statistics, and analyze the data to uncover fan film preferences.
Analyzing NYC High School Data
For this project, you'll assume the role of a data scientist analyzing relationships between SAT scores and demographic factors in NYC public schools to determine if the SAT is a fair test.
Exploring eBay Car Sales Data
For this project, we'll assume the role of data analysts for a used car classifieds service to explore and clean a dataset of car listings from eBay Kleinanzeigen, a section of the German eBay website.
Clean and Analyze Employee Exit Surveys
For this project, we'll assume the role of data analysts for the Department of Education, Training and Employment and the Technical and Further Education institute in Queensland, Australia to analyze employee exit surveys and uncover insights about why employees resign.
Profitable App Profiles for the App Store and Google Play Markets
For this project, you'll be a data analyst at a company that builds free, ad-supported Android and iOS apps. To drive revenue, you'll analyze real app market data to find app profiles that attract the most users.
+ 3 more projects throughout the path
Earn your Data Cleaning with Python Certificate
Add this Python certificate to your resume or LinkedIn to showcase your skills and stand out in job applications.
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Go from zero to job-ready
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Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
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Work with real data from day one with interactive lessons and hands-on exercises.
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